A major bottleneck in devising effective targeted therapies for cancer treatment lies at the identification of relevant drug targets. Genetic screens that measure the outcome of inhibiting individual genes in cancer cells and in normal cells on a genome-scale are powerful experiments that could identify such drug targets. Until recently these screens could not be performed in human cells. To perform such screens, my laboratory has developed new methods, based on the principle of RNA interference (RNAi), to individually inactivate every gene in the human genome, approximately 32,000 genes, one at a time. Furthermore, we have developed technologies to carry out these screens in high throughput fashion. Through this funding opportunity, I aim to further develop our RNAi technology platform to enhance its throughput and fidelity. I will use lung cancer cell lines as a discovery paradigm for this technology development effort. The ultimate goal is to enable the genome-wide interrogation of large numbers of cancer cell lines to comprehensively identify the dependencies and vulnerabilities specific to cancer cells but not normal cells. This approach should uncover many previously unrecognized targets for drug discovery and has the potential to provide additional, more effective treatment options for cancer patients.